GDP

library(tidyverse)

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## ✔ tibble  3.1.7     ✔ dplyr   1.0.9
## ✔ tidyr   1.2.0     ✔ stringr 1.4.0
## ✔ readr   2.1.2     ✔ forcats 0.5.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

library(plotly)

## 
## 载入程辑包：'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
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##     filter

## The following object is masked from 'package:graphics':
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##     layout

library(here)

## here() starts at D:/internship/internship-reproductive-rights

library(readr)
library(ggplot2)
library(themes360info)

## Warning: ! Preferred font, ITC Franklin Gothic, not found. Using Libre Franklin as a
##   fallback.
## ℹ Specify a different font to use with 360info themes by calling
##   register_360fonts() or by setting options("themes360info.franklin.pref") to
##   either "itc" or "libre" (or "none" to disable automatic font loading).

library(dplyr)

fertility_develop <- read_csv(here("data", "fertility_development.csv")) %>% 
pivot_longer(-Region,names_to = "Years", values_to = "number")

## Rows: 7 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (1): Region
## dbl (14): 1955, 1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, ...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

line_develop<- ggplot(fertility_develop, aes(x = Years, y = number, color = Region)) +geom_point()+
  geom_line(aes(group = 1))+
  # facet_wrap(~Region) +
  theme_bw() + theme(axis.text.x = element_text(angle = 90)) +
  ggtitle("Trend for number of birth of each development group
")

ggplotly(line_develop)

#数据解释看fertility的数据的最后一页

fertility_income <- read_csv(here("data", "worldbank_incomegroup.csv")) %>% 
pivot_longer(-Region,names_to = "Years", values_to = "number")

## Rows: 6 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (1): Region
## dbl (14): 1955, 1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, ...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

line_income<- ggplot(fertility_income, aes(x = Years, y = number, color = Region)) +
  # geom_point()+
  geom_line(aes(group = 1))+
  # facet_wrap(~Region) +
  theme_bw() + theme(axis.text.x = element_text(angle = 90)) +
  ggtitle("Trend for each continent over time of top 5 key crop yields")

ggplotly(line_income)

#数据解释看fertility的数据的最后一页

fertility_geographic <- read_csv(here("data", "worldbank_geographic.csv")) %>% 
pivot_longer(-Region,names_to = "Years", values_to = "number")

## Rows: 6 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (1): Region
## dbl (14): 1955, 1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, ...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

line_geo<- ggplot(fertility_geographic, aes(x = Years, y = number, color = Region)) +
  # geom_point()+
  geom_line(aes(group = 1))+
  # facet_wrap(~Region) +
  theme_bw() + theme(axis.text.x = element_text(angle = 90)) +
  ggtitle("Trend for each continent over time of top 5 key crop yields")+theme_360()

ggplotly(line_geo)

把这几张图放一起